Worldwide energy demand has been growing steadily during the past five decades and most experts believe that this trend will continue to rise. The amount of emitted harmful emission gases increases in parallel with increasing energy consumption. This increase has forced many countries to take various precautions, and various restrictions on emitted emissions have been carried. In this study, effects of addition of oxygen containing nanoparticle additives to biodiesel on fuel properties and effects on diesel engine performance and exhaust emissions were investigated. Two different nanoparticle additives, namely MgO and SiO₂, were added to biodiesel at the addition dosage of 25 and 50 ppm. Fuel properties, engine performance, and exhaust emission characteristics of obtained modified fuels were examined. As a result of this study, engine emission values NO_x and CO were decreased and engine performance values slightly increased with the addition of nanoparticle additives.

In this study, emissions of compression ignition engine fueled by diesel fuel with nanoparticle additives was modeled by regression analysis, artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) methods. Cetane number (CN) and engine speed (rpm) were selected as input parameters for estimation of carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) emissions. The results of estimation techniques were compared with each other and they showed that regression analysis was not accurate enough for prediction. On the other hand, ANN and ANFIS modelling techniques gave more accurate results with respect to regression analysis; linear and non-linear. Especially ANFIS models can be suggested as estimation method with minimum error compared to experimental results.

This study focused experimentally on the evaluation of a higher alcohol biofuel utilization with diesel fuel in a compression ignition engine. To this effect, two different ternary higher alcohol biofuel blends with different percentages by volume were used, i.e., DA5 (85% diesel + 5% butanol +5% pentanol + 5% hexanol) and DA10 (70% diesel + 10% butanol + 10% pentanol + 10% hexanol). The performance and emission results were compared against reference standard diesel fuel. Experiments revealed the brake power (BP) values of the engine to be reduced due to the lower calorific value of the alcohols. In addition, this phenomenon led to increased levels of brake-specific fuel consumption (BSFC), which resulted in a higher fuel consumption to obtain unit power. Regarding emissions, carbon monoxide (CO) was reduced as a result of the additional oxygen content of alcohols, which triggered the more oxidized CO with oxygen. The results regarding unwanted nitrogen oxides (NOx) emissions were also attractive according to the alcohol utilized. Considerable reductions were obtained with alcohol mixtures when compared to diesel fuel, which can be explained by the reduced combustion temperatures in the cylinder, given the higher latent heat in the evaporation of alcohols.

This study explores the effects of electrically assisted turbochargers (EAT) on the performance of diesel engines by incorporating an electrical motor/generator into a conventional turbocharged model. The engine simulations were conducted at three different power levels of 2, 2.5, and 3 kW to assess the impact of electrical assistance. The results demonstrated that EAT significantly boosts engine performance, with an increase in boost pressure of up to 58.9% at 1000 rpm and an average increase of 30.9% across the low engine speed range (1000–2200 rpm). Additionally, the maximum turbocharger speed was achieved at lower engine speeds, dropping from 2400 rpm to as low as 1600 rpm with 3 kW assistance. Engine torque improved by up to 28.2% at 1000 rpm, and brake-specific fuel consumption (BSFC) was reduced by as much as 8.1%. Transient simulations showed notable improvements in response times, with turbo lag reduced by up to 53% under acceleration conditions. Overall, EAT technology provides significant enhancements in engine efficiency, torque output, fuel economy, and transient response, positioning it as a promising solution for improving diesel engine performance, particularly in addressing turbo lag and low-speed inefficiencies.

Growing concerns surrounding global warming and environmental degradation have prompted the widespread adoption of various emission control methodologies, with a particular emphasis on reducing nitrogen oxide (NOx) emissions. Selective catalytic reduction (SCR) stands out as a highly effective technique, applicable not only to large-scale industrial machinery but also to smaller vehicles, aimed at converting NOx emissions into less harmful nitrogen (N2) using specialized catalysts and reductants. This particular study focuses on synthesizing copper-based Y zeolite and conducting experiments using ethanol as a reductant in the exhaust stream of a two-cylinder diesel engine operating under different loads. Furthermore, the catalyst was subjected to thorough characterization using techniques such as Scanning Electron Microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS), X-ray Diffraction (XRD), and Brunauer-Emmet-Teller (BET) analysis. Results indicate that as temperature and engine load increase, the efficiency of NOx conversion also improves. The highest conversion rate, reaching 94.67%, was achieved at 260°C under a 5 kW load. Additionally, average conversion rates of 90%, 90.70%, and 92.62% were observed for loads of 1 kW, 3 kW, and 5 kW, respectively. These findings not only highlight the effectiveness of SCR technology in reducing NOx emissions but also underscore the potential of copper-based Y zeolite catalysts in this regard. The comprehensive characterization of the catalyst provides valuable insights into its structural and chemical properties, paving the way for further advancements in emission control strategies.

In this study, performance and emission characteristics of sunflower oil methyl esters (sunflower oil biodiesel/SOB) and diesel were studied in between 1400-2600 engine speed. After determining fuel properties, performance and emissions of the test engine, energy and exergy analysis were conducted by using experimental data attained from the experiments. Analyses were performed at 1800 rpm (revolutions per minute) engine speed which gave maximum torque value. With the aid of experimental data and energy balances and exergy rates for the determined control volume which is the whole engine, first and second law efficiencies related with namely quantity and quality were determined for the test fuels, SOB and diesel fuel. Conclusions were evaluated to determine the effects of test fuels on 1^st law and 2^nd law efficiency performance.